Co-optimization of CO2-EOR and Storage Processes under Geological Uncertainty

Ampomah, William; Balch, Robert; Will, Robert; Cather, Martha; Gunda, Dhiraj; Dai, Zhenxue

doi:10.1016/j.egypro.2017.03.1835

Cited by 31 publications

(20 citation statements)

References 56 publications

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“…Three-dimensional (3-D) reservoir geological modeling is currently an effective method for evaluating the CO 2 storage capacity. Several recent studies have examined the CO 2 storage capacity using 3-D geological models (Ampomah et al 2017a;Anderson 2017;Spencer 1987;Alcalde et al 2018). These models are an appropriate approach that integrates all available geological, geophysical, and engineering data (Hirsche et al 1997;Bueno et al 2011;Abdideh and Bargahi 2012;Dai et al 2016).…”

Section: Introductionmentioning

confidence: 99%

CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

AlRassas

Ren

Sun

et al. 2021

J Petrol Explor Prod Technol

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Underground CO2 storage is a promising technology for mitigating climate change. In this vein, the subsurface condition was inherited a lot of uncertainties that prevent the success of the CO2 storage project. Therefore, this study aims to build the 3D model under geological uncertainties for enhancing CO2 storage capacity in the Shahejie Formation (Es1), Nv32 block, China. The well logs, seismic data, and geological data were used for the construction of 3-D petrophysical models. The target study area model focused on four units (Es1 × 1, Es1 × 2, Es1 × 3, and Es1 × 4) in the Shahejie Formation. Well logs were utilized to predict petrophysical properties; the lithofacies indicated that the Shahejie Formation units are sandstone, shale, and limestone. Also, the petrophysical interpretation demonstrated that the $$Es1$$ E s 1 reservoir exhibited high percentage porosity, permeability, and medium to high net-to-gross ratios. The static model showed that there are lateral heterogeneities in the reservoir properties and lithofacies; optimal reservoir rocks exist in Es1 × 4, Es1 × 3, and Es1 × 2 units. Moreover, the pore volume of the Es1 unit was estimated from petrophysical property models, ranging between 0.554369 and 10.03771 × 106 sm3, with a total volumetric value of 20.0819 × 106 sm3 for the four reservoir units. Then, the 100–400 realizations were generated for the pore volume uncertainties assessment. In consequence, 200 realizations were determined as an optimal solution for capturing geological uncertainties. The estimation of CO2 storage capacity in the Es1 formation ranged from 15.6 to 207.9 × 109 t. This result suggests the potential of CO2 geological storage in the Shahejie Formation, China.

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Section: Introductionmentioning

confidence: 99%

CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

AlRassas

Ren

Sun

et al. 2021

J Petrol Explor Prod Technol

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“…The response surface method (RSM) uses a second-order mathematical model between the response output and influencing factors as an approximation of the true functional relationship based on statistical analysis. 10 , 11 The RSM has been widely used in research fields such as electronics, machinery, agriculture, the chemical industry, and industrial process improvement 12 and has also been used in the petroleum industry research field in recent years. 13 − 16 The Box–Behnken design (BBD) and central composite design (CCD) are the most common designs of the response surface methodology and have been widely used in various experiments.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Factors Affecting Polymer Flooding Based on a Response Surface Method

2021

ACS Omega

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Both polymer injection time and injection rate play an important role in the development of an offshore reservoir with a limited service life of the platform. To quantitatively and qualitatively investigate the influence of the formation packing sequence, injection rate, polymer injection timing, and their interaction on the performance of polymer flooding, a numerical reservoir model is simulated in this study based on the properties of offshore reservoir LD in China. Also, the polymer flooding experimental scheme is designed according to the response surface method and single-factor analysis method. Based on numerical simulation and statistical analysis, a regression model is established to predict the incremental oil recovery factor of polymer flooding. The analysis of variance (ANOVA) shows that the regression model fits well with the experimental data. The three factors’ influence capacities on the increased oil recovery factor from large to small are the injection rate, formation rhythm, and injection timing. From the analysis, it is also found that the improved polymer flooding performance can be achieved under an injection rate of 0.07–0.09 PV/a and an injection timing of 30% water cut for positive rhythm formation.

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“…Moreover, injecting CO2 into an oil-bearing formation has the potential to enhance oil recovery. This technique, hereinafter referred to as CO2-EOR, coupled/associated with the gas storage can defray the cost of sequestration (Hill et al 2013;Ettehadtavakkol et al 2014;Ampomah et al 2017;Lee et al 2019). The CO2-EOR and its storage potential have been investigated by many projects worldwide (Bachu, 2018;Choi et al, 2013;Nguyen-Trinh and Ha-Duong, 2015;Pham and Halland, 2017;Wei et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Integrated workflow in 3D geological model construction for evaluation of CO2 storage capacity of a fractured basement reservoir in Cuu Long Basin, Vietnam

Thanh

Sugai

Nguele

et al. 2019

International Journal of Greenhouse Gas Control

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Carbon dioxide (CO2) capture, utilization, and storage (CCUS) have been proposed as a possible technique to mitigate climate change. In this vein, CO2 storage through enhanced oil recovery (EOR) in depleted hydrocarbon reservoirs is touted as a most effective approach because it synergistically increases oil production and enables permanent sequestration into the reservoirs.However, the construction of a reasonable 3D geological model for this storage reservoir is a major challenge. Thus, this study presents an efficient workflow for constructing an accurate geological model for the evaluation of CO2 storage capacity in a fractured basement reservoir in the Cuu Long Basin, Vietnam. Artificial neural network (ANN) has been used to predict porosity and permeability values through seismic attributes and well log data. The predicted values were selected using high correlation factors with well log data. Subsequently, the Sequential Gaussian Simulation and co-kriging methods were applied to generate a 3D static geological model by using azimuth and dip parameters. Finally, drill stem test matching was performed to validate the accuracy of the porosity and permeability models through dynamic simulation. A validation 3D reservoir model, which integrates geophysical, geological, and engineering data from fractured basement formation in Cuu Long Basin, was further constructed to calculate theoretical CO2 storage capacity. As a result, the calculated storage capacity for the fractured basement reservoir ranged from 7.02 to 99.5 million metric tons. These estimated results demonstrate that fractured basement reservoir has a combined potential for CO2 storage and EOR in the Cuu Long Basin.

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Co-optimization of CO2-EOR and Storage Processes under Geological Uncertainty

Cited by 31 publications

References 56 publications

CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

CO2 storage capacity estimation under geological uncertainty using 3-D geological modeling of unconventional reservoir rocks in Shahejie Formation, block Nv32, China

Analysis of Factors Affecting Polymer Flooding Based on a Response Surface Method

Integrated workflow in 3D geological model construction for evaluation of CO2 storage capacity of a fractured basement reservoir in Cuu Long Basin, Vietnam

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